diff --git a/src/AzureExtension/Contracts/IAzureOpenAIService.cs b/src/AzureExtension/Contracts/IAzureOpenAIService.cs
index 3ec92887..84f936e7 100644
--- a/src/AzureExtension/Contracts/IAzureOpenAIService.cs
+++ b/src/AzureExtension/Contracts/IAzureOpenAIService.cs
@@ -1,6 +1,6 @@
-// Copyright (c) Microsoft Corporation.
-// Licensed under the MIT License.
-
+// Copyright (c) Microsoft Corporation.
+// Licensed under the MIT License.
+
 namespace DevHomeAzureExtension.Contracts;
 
 public enum OpenAIEndpoint
@@ -10,16 +10,16 @@ public enum OpenAIEndpoint
 }
 
 public delegate IAzureOpenAIService AzureOpenAIServiceFactory(OpenAIEndpoint endpoint);
-
-public interface IAzureOpenAIService
+
+public interface IAzureOpenAIService
 {
     public IAICredentialService AICredentialService { get; }
 
     public void InitializeAIClient();
 
-    public Uri GetEmbeddingsFile();
-
-    public ReadOnlyMemory<float> GetEmbedding(string inputText);
-
+    public Uri GetEmbeddingsFile();
+
+    public ReadOnlyMemory<float> GetEmbedding(string inputText);
+
     public Task<string> GetAICompletionAsync(string systemInstructions, string userMessage);
-}
+}
diff --git a/src/AzureExtension/QuickStartPlayground/EmbeddingsCalc.cs b/src/AzureExtension/QuickStartPlayground/EmbeddingsCalc.cs
index da44b0f8..2bcfc5c0 100644
--- a/src/AzureExtension/QuickStartPlayground/EmbeddingsCalc.cs
+++ b/src/AzureExtension/QuickStartPlayground/EmbeddingsCalc.cs
@@ -1,77 +1,77 @@
-// Copyright (c) Microsoft Corporation.
-// Licensed under the MIT License.
-
-using System.Globalization;
-using System.Numerics.Tensors;
-
-namespace DevHomeAzureExtension.QuickStartPlayground;
-
-/// <summary>
-/// This class contains helper methods to perform vector database-like operations on the
-/// sample projects. The extension uses this class to help find the reference sample that should
-/// be used for the user's prompt.
-/// </summary>
-public static class EmbeddingsCalc
-{
-    private static double CalcCosineSimilarity(ReadOnlyMemory<float> a, ReadOnlyMemory<float> b)
-    {
-        try
-        {
-            return TensorPrimitives.CosineSimilarity(a.Span, b.Span);
-        }
-        catch (Exception)
-        {
-            return 0;
-        }
-    }
-
-    public static List<(double CosineSimilarity, TrainingSample Sample)> SortByLanguageThenCosine(List<(double CosineSimilarity, TrainingSample Sample)> trainingSamples, string recommendedLanguage)
-    {
-        // Convert the recommendedLanguage to lowercase for case-insensitive comparison
-        recommendedLanguage = recommendedLanguage.ToLower(CultureInfo.InvariantCulture);
-
-        // Clone the list of docs to avoid modifying the original list
-        var similarDocList = trainingSamples.ToList();
-
-        // Sort doc list to rank highest any projects with the same language as recommended
-        similarDocList.Sort((a, b) =>
-        {
-            // Sort by recommended language (case-insensitive) first
-            var aHasRecommendedLang = a.Sample.Language != null ? a.Sample.Language.Equals(recommendedLanguage, StringComparison.OrdinalIgnoreCase) : false;
-            var bHasRecommendedLang = b.Sample.Language != null ? b.Sample.Language.Equals(recommendedLanguage, StringComparison.OrdinalIgnoreCase) : false;
-
-            if (aHasRecommendedLang && !bHasRecommendedLang)
-            {
-                return -1;
-            }
-            else if (!aHasRecommendedLang && bHasRecommendedLang)
-            {
-                return 1;
-            }
-
-            // If recommended languages are the same or both are different from the recommended language,
-            // then sort by cosine similarity in descending order
-            return b.CosineSimilarity.CompareTo(a.CosineSimilarity);
-        });
-
-        return similarDocList;
-    }
-
-    public static List<(double CosineSimilarity, TrainingSample Sample)> GetCosineSimilaritySamples(ReadOnlyMemory<float> questionEmbedding, IReadOnlyList<TrainingSample> trainingSamples)
-    {
-        // For each doc in docs, calculate the cosine similarity between the question embedding and the doc embedding
-        // Sort the docs by the cosine similarity value
-        var cosineSimilarityDocs = new List<(double CosineSimilarity, TrainingSample Sample)>();
-
-        for (var i = 0; i < trainingSamples.Count; i++)
-        {
-            var sample = trainingSamples[i] ?? throw new ArgumentOutOfRangeException($"Document {i} is not expected to not be null");
-            var cosineSimilarity = CalcCosineSimilarity(questionEmbedding, sample.Embedding);
-            cosineSimilarityDocs.Add((cosineSimilarity, sample));
-        }
-
-        cosineSimilarityDocs.Sort((a, b) => b.CosineSimilarity.CompareTo(a.CosineSimilarity));
-
-        return cosineSimilarityDocs;
-    }
-}
+// Copyright (c) Microsoft Corporation.
+// Licensed under the MIT License.
+
+using System.Globalization;
+using System.Numerics.Tensors;
+
+namespace DevHomeAzureExtension.QuickStartPlayground;
+
+/// <summary>
+/// This class contains helper methods to perform vector database-like operations on the
+/// sample projects. The extension uses this class to help find the reference sample that should
+/// be used for the user's prompt.
+/// </summary>
+public static class EmbeddingsCalc
+{
+    private static double CalcCosineSimilarity(ReadOnlyMemory<float> a, ReadOnlyMemory<float> b)
+    {
+        try
+        {
+            return TensorPrimitives.CosineSimilarity(a.Span, b.Span);
+        }
+        catch (Exception)
+        {
+            return 0;
+        }
+    }
+
+    public static List<(double CosineSimilarity, TrainingSample Sample)> SortByLanguageThenCosine(List<(double CosineSimilarity, TrainingSample Sample)> trainingSamples, string recommendedLanguage)
+    {
+        // Convert the recommendedLanguage to lowercase for case-insensitive comparison
+        recommendedLanguage = recommendedLanguage.ToLower(CultureInfo.InvariantCulture);
+
+        // Clone the list of docs to avoid modifying the original list
+        var similarDocList = trainingSamples.ToList();
+
+        // Sort doc list to rank highest any projects with the same language as recommended
+        similarDocList.Sort((a, b) =>
+        {
+            // Sort by recommended language (case-insensitive) first
+            var aHasRecommendedLang = a.Sample.Language != null ? a.Sample.Language.Equals(recommendedLanguage, StringComparison.OrdinalIgnoreCase) : false;
+            var bHasRecommendedLang = b.Sample.Language != null ? b.Sample.Language.Equals(recommendedLanguage, StringComparison.OrdinalIgnoreCase) : false;
+
+            if (aHasRecommendedLang && !bHasRecommendedLang)
+            {
+                return -1;
+            }
+            else if (!aHasRecommendedLang && bHasRecommendedLang)
+            {
+                return 1;
+            }
+
+            // If recommended languages are the same or both are different from the recommended language,
+            // then sort by cosine similarity in descending order
+            return b.CosineSimilarity.CompareTo(a.CosineSimilarity);
+        });
+
+        return similarDocList;
+    }
+
+    public static List<(double CosineSimilarity, TrainingSample Sample)> GetCosineSimilaritySamples(ReadOnlyMemory<float> questionEmbedding, IReadOnlyList<TrainingSample> trainingSamples)
+    {
+        // For each doc in docs, calculate the cosine similarity between the question embedding and the doc embedding
+        // Sort the docs by the cosine similarity value
+        var cosineSimilarityDocs = new List<(double CosineSimilarity, TrainingSample Sample)>();
+
+        for (var i = 0; i < trainingSamples.Count; i++)
+        {
+            var sample = trainingSamples[i] ?? throw new ArgumentOutOfRangeException($"Document {i} is not expected to not be null");
+            var cosineSimilarity = CalcCosineSimilarity(questionEmbedding, sample.Embedding);
+            cosineSimilarityDocs.Add((cosineSimilarity, sample));
+        }
+
+        cosineSimilarityDocs.Sort((a, b) => b.CosineSimilarity.CompareTo(a.CosineSimilarity));
+
+        return cosineSimilarityDocs;
+    }
+}